货车流量大数据在区域消费总额预测中的应用

Application of Truck Flow Big Data in Forecasting Regional Consumption

摘要:

为了探索使用交通流量数据预测消费变动，以更好地助力精准施策，促进消费的恢复和提升，以福建省内高速公路收费站产生的4.85亿条货车过站记录为基础，归总形成2017—2023年福州市内部、以及它与福建省其他8个地级市之间的货车流量月度数据。在总结时序和截面特征的基础上，分析货车流量与消费的相关性，并采用交乘项回归模型考察疫情前后的相关性差异。进一步选取其中相关性较高的货车流量指标，使用普通最小二乘法（OLS）与向量自回归模型（VAR）等构建福州市社会消费品零售总额的预测模型。结果发现：流入福州市的车流总量与福州市的消费总量走势相似，2020年前平稳增长，此后明显下滑，两者同比增长率有很高的相关性；回归结果中，多数地级市流入福州市的货车流量与福州市的当期消费总量呈正相关，而这种相关性在2020年后有所减弱；相比于OLS方法，多变量VAR模型的预测精度更高，绝对误差小于1%的概率能够达到近95%，可实现对福州市月度消费总量提前预测。

关键词:运输经济;经济预测;高速公路;货车流量;社会消费品零售总额

Abstract:

This study aims to predict consumption changes， which can help precise policymaking， further promote the recovery of consumption. Based on 485 million truck crossing records generated by highway toll stations in Fujian Province， we combed monthly truck flow data from 2017 to 2023 within Fuzhou City， as well as between it and 8 other prefecture-level cities in Fujian Province. Firstly， we summarize the time-series and cross-sectional features to analyze the correlation between truck flow and consumption. And then we use regression model to examine the correlation differences before and after 2020. Furthermore， we select the truck flow indicators with higher correlation in the above analysis， using Ordinary Least Squares （OLS） method and Vector Autoregressive （VAR） model to construct a prediction model of the Total Retail Sales in Fuzhou City. The results indicate that the truck flow and the total consumption of Fuzhou City show a similar trend， growing steadily before 2020 and declining significantly afterward. And the year-on-year percentage of both are highly correlated. The empirical results show that the truck flow from most prefecture-level cities into Fuzhou City is positively correlated with the total retail sales of Fuzhou City， and this correlation is weakened after 2020. Compared with the OLS method， the multivariate VAR model has a higher prediction accuracy with its probability of absolute error less than 1 pct reaching nearly 95%， which allows for the advance prediction of the monthly total consumption in Fuzhou City.

Key words:transportation economy;economic forecast;highway;truck flow;the total retail sales